9 citations · 24 across the 20 of their papers we have counts for
20 papers
APD-Agents: A Large Language Model-Driven Multi-Agents Collaborative Framework for Automated Page Design
Xinpeng Chen, Xiaofeng Han, Kaihao Zhang +6
Layout design is a crucial step in developing mobile app pages. However, crafting satisfactory designs is time-intensive for designers: they need to consider which controls and con…
HieroAction: Hierarchically Guided VLM for Fine-Grained Action Analysis
Junhao Wu, Xiuer Gu, Zhiying Li +6
Evaluating human actions with clear and detailed feedback is important in areas such as sports, healthcare, and robotics, where decisions rely not only on final outcomes but also o…
SatDreamer360: Multiview-Consistent Generation of Ground-Level Scenes from Satellite Imagery
Xianghui Ze, Beiyi Zhu, Zhenbo Song +2
Generating multiview-consistent ground-level scenes from satellite imagery is a challenging task with broad applications in simulation, autonomous navigation, and digit…
Controllable Satellite-to-Street-View Synthesis with Precise Pose Alignment and Zero-Shot Environmental Control
Xianghui Ze, Zhenbo Song, Qiwei Wang +2
Generating street-view images from satellite imagery is a challenging task, particularly in maintaining accurate pose alignment and incorporating diverse environmental conditions.…
AS-FIBA: Adaptive Selective Frequency-Injection for Backdoor Attack on Deep Face Restoration
Zhenbo Song, Wenhao Gao, Zhenyuan Zhang +1
Deep learning-based face restoration models, increasingly prevalent in smart devices, have become targets for sophisticated backdoor attacks. These attacks, through subtle trigger…
Adversarial Purification and Fine-tuning for Robust UDC Image Restoration
Zhenbo Song, Zhenyuan Zhang, Kaihao Zhang +2
This study delves into the enhancement of Under-Display Camera (UDC) image restoration models, focusing on their robustness against adversarial attacks. Despite its innovative appr…
STDG: Semi-Teacher-Student Training Paradigram for Depth-guided One-stage Scene Graph Generation
Xukun Zhou, Zhenbo Song, Jun He +2
Scene Graph Generation is a critical enabler of environmental comprehension for autonomous robotic systems. Most of existing methods, however, are often thwarted by the intricate d…
Learning Dense Flow Field for Highly-accurate Cross-view Camera Localization
Zhenbo Song, Xianghui Ze, Jianfeng Lu +1
This paper addresses the problem of estimating the 3-DoF camera pose for a ground-level image with respect to a satellite image that encompasses the local surroundings. We propose…
Benchmarking Ultra-High-Definition Image Reflection Removal
Zhenyuan Zhang, Zhenbo Song, Kaihao Zhang +2
Deep learning based methods have achieved significant success in the task of single image reflection removal (SIRR). However, the majority of these methods are focused on High-Defi…
EmoTalk: Speech-Driven Emotional Disentanglement for 3D Face Animation
Ziqiao Peng, Haoyu Wu, Zhenbo Song +5
Speech-driven 3D face animation aims to generate realistic facial expressions that match the speech content and emotion. However, existing methods often neglect emotional facial ex…
SHLE: Devices Tracking and Depth Filtering for Stereo-based Height Limit Estimation
Zhaoxin Fan, Kaixing Yang, Min Zhang +3
Recently, over-height vehicle strike frequently occurs, causing great economic cost and serious safety problems. Hence, an alert system which can accurately discover any possible h…
FuRPE: Learning Full-body Reconstruction from Part Experts
Zhaoxin Fan, Yuqing Pan, Hao Xu +5
In the field of full-body reconstruction, the scarcity of annotated data often impedes the efficacy of prevailing methods. To address this issue, we introduce FuRPE, a novel framew…
GIDP: Learning a Good Initialization and Inducing Descriptor Post-enhancing for Large-scale Place Recognition
Zhaoxin Fan, Zhenbo Song, Hongyan Liu +1
Large-scale place recognition is a fundamental but challenging task, which plays an increasingly important role in autonomous driving and robotics. Existing methods have achieved a…
MonoSIM: Simulating Learning Behaviors of Heterogeneous Point Cloud Object Detectors for Monocular 3D Object Detection
Han Sun, Zhaoxin Fan, Zhenbo Song +3
Monocular 3D object detection is a fundamental but very important task to many applications including autonomous driving, robotic grasping and augmented reality. Existing leading m…
Object Level Depth Reconstruction for Category Level 6D Object Pose Estimation From Monocular RGB Image
Zhaoxin Fan, Zhenbo Song, Jian Xu +4
Recently, RGBD-based category-level 6D object pose estimation has achieved promising improvement in performance, however, the requirement of depth information prohibits broader app…
ACR-Pose: Adversarial Canonical Representation Reconstruction Network for Category Level 6D Object Pose Estimation
Zhaoxin Fan, Zhengbo Song, Jian Xu +4
Recently, category-level 6D object pose estimation has achieved significant improvements with the development of reconstructing canonical 3D representations. However, the reconstru…
RPR-Net: A Point Cloud-based Rotation-aware Large Scale Place Recognition Network
Zhaoxin Fan, Zhenbo Song, Wenping Zhang +3
Point cloud-based large scale place recognition is an important but challenging task for many applications such as Simultaneous Localization and Mapping (SLAM). Taking the task as…
SVT-Net: Super Light-Weight Sparse Voxel Transformer for Large Scale Place Recognition
Zhaoxin Fan, Zhenbo Song, Hongyan Liu +3
Point cloud-based large scale place recognition is fundamental for many applications like Simultaneous Localization and Mapping (SLAM). Although many models have been proposed and…
Incorporating Orientations into End-to-end Driving Model for Steering Control
Peng Wan, Zhenbo Song, Jianfeng Lu
In this paper, we present a novel end-to-end deep neural network model for autonomous driving that takes monocular image sequence as input, and directly generates the steering cont…
End-to-end Learning for Inter-Vehicle Distance and Relative Velocity Estimation in ADAS with a Monocular Camera
Zhenbo Song, Jianfeng Lu, Tong Zhang +1
Inter-vehicle distance and relative velocity estimations are two basic functions for any ADAS (Advanced driver-assistance systems). In this paper, we propose a monocular camera-bas…